Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW

🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .

🛰️ An approximate nearest-neighbor search library for Python and Java with a focus on ease of use, simplicity, and deployability.

PostgreSQL vector database extension for building AI applications

RAG Time: A 5-week Learning Journey to Mastering RAG

一款简单好用的 跨平台/多语言的 相似向量/相似词/相似句 高性能检索引擎。欢迎star & fork。Build together! Power another !

Visualize hnsw, faiss and other anns index

Fast, SQL powered, in-process vector search for any language with an SQLite driver

Fast approximate nearest neighbor searching in Rust, based on HNSW index

Lightweight Nearest Neighbors with Flexible Backends

Vector search engine inside Milvus, integrating FAISS, HNSW, DiskANN.

Graph-based Approximate Nearest Neighbor Search

Client Side Vector Database

NornicDB is a high-performance graph + vector database built for AI agents and knowledge systems. It speaks Neo4j's (Bolt + Cypher) and qdrant's (gRPC) languages so you can use Nornic with zero code changes, while adding intelligent features including a graphql endpoint, air-gapped embeddings, GPU accelerated search, and other intelligent features.

⚡ A fast embedded library for approximate nearest neighbor search

Endee.io – A high-performance vector database, designed to handle up to 1B vectors on a single node, delivering significant performance gains through optimized indexing and execution. Also available in cloud https://endee.io/